Cover Image

Self Adaptive Threshold Pseudo-labeling and Unreliable Sample Contrastive Loss for Semi-supervised Image Classification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Xuerong, Huang, Li, Lv, Jing, Yang, Ming
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Semi-supervised Video Semantic Segmentation Using Unreliable Pseudo Labels for PVUW2024
by: Wu, Biao, et al.
Published: (2024)

A Channel-ensemble Approach: Unbiased and Low-variance Pseudo-labels is Critical for Semi-supervised Classification
by: Wu, Jiaqi, et al.
Published: (2024)

Semi-LLIE: Semi-supervised Contrastive Learning with Mamba-based Low-light Image Enhancement
by: Li, Guanlin, et al.
Published: (2024)

Semi-Supervised Dual-Threshold Contrastive Learning for Ultrasound Image Classification and Segmentation
by: Zhang, Peng, et al.
Published: (2025)

Robust Noisy Pseudo-label Learning for Semi-supervised Medical Image Segmentation Using Diffusion Model
by: Xi, Lin, et al.
Published: (2025)

Leveraging Fixed and Dynamic Pseudo-labels for Semi-supervised Medical Image Segmentation
by: Kumari, Suruchi, et al.
Published: (2024)

Semi-Supervised Hyperspectral Image Classification with Edge-Aware Superpixel Label Propagation and Adaptive Pseudo-Labeling
by: Qiu, Yunfei, et al.
Published: (2026)

RePL: Pseudo-label Refinement for Semi-supervised LiDAR Semantic Segmentation
by: Kwon, Donghyeon, et al.
Published: (2026)

Energy Score-based Pseudo-Label Filtering and Adaptive Loss for Imbalanced Semi-supervised SAR target recognition
by: Zhang, Xinzheng, et al.
Published: (2024)

Uncertainty-aware Long-tailed Weights Model the Utility of Pseudo-labels for Semi-supervised Learning
by: Wu, Jiaqi, et al.
Published: (2025)

Trust the Unreliability: Inward Backward Dynamic Unreliability Driven Coreset Selection for Medical Image Classification
by: Liang, Yan, et al.
Published: (2026)

Towards Adaptive Pseudo-label Learning for Semi-Supervised Temporal Action Localization
by: Zhou, Feixiang, et al.
Published: (2024)

SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning
by: Zhao, Shuai, et al.
Published: (2025)

Decoupled Pseudo-labeling for Semi-Supervised Monocular 3D Object Detection
by: Zhang, Jiacheng, et al.
Published: (2024)

Judge Like a Real Doctor: Dual Teacher Sample Consistency Framework for Semi-supervised Medical Image Classification
by: Qixiang, Zhang, et al.
Published: (2024)

PCSR: Pseudo-label Consistency-Guided Sample Refinement for Noisy Correspondence Learning
by: Liu, Zhuoyao, et al.
Published: (2025)

Dual Cross-image Semantic Consistency with Self-aware Pseudo Labeling for Semi-supervised Medical Image Segmentation
by: Wu, Han, et al.
Published: (2025)

MetaSSP: Enhancing Semi-supervised Implicit 3D Reconstruction through Meta-adaptive EMA and SDF-aware Pseudo-label Evaluation
by: Zhang, Luoxi, et al.
Published: (2026)

Uncertainty-aware Sampling for Long-tailed Semi-supervised Learning
by: Yang, Kuo, et al.
Published: (2024)

Using Unreliable Pseudo-Labels for Label-Efficient Semantic Segmentation
by: Wang, Haochen, et al.
Published: (2023)

ALFred: An Active Learning Framework for Real-world Semi-supervised Anomaly Detection with Adaptive Thresholds
by: Yao, Shanle, et al.
Published: (2025)

Intra-Class Subdivision for Pixel Contrastive Learning: Application to Semi-supervised Cardiac Image Segmentation
by: Zhao, Jiajun, et al.
Published: (2026)

Adaptive Spatial Augmentation for Semi-supervised Semantic Segmentation
by: Ran, Lingyan, et al.
Published: (2025)

Pseudo-label refinement using superpixels for semi-supervised brain tumour segmentation
by: Thompson, Bethany H., et al.
Published: (2021)

Color-$S^{4}L$: Self-supervised Semi-supervised Learning with Image Colorization
by: Chen, Hanxiao
Published: (2024)

Improving Pseudo-labelling and Enhancing Robustness for Semi-Supervised Domain Generalization
by: Khan, Adnan, et al.
Published: (2024)

Boundary-aware Contrastive Learning for Semi-supervised Nuclei Instance Segmentation
by: Zhang, Ye, et al.
Published: (2024)

NimbleD: Enhancing Self-supervised Monocular Depth Estimation with Pseudo-labels and Large-scale Video Pre-training
by: Luginov, Albert, et al.
Published: (2024)

ARMA-C3: A Contrastive ARMA Convolutional Framework for Unsupervised and Semi-supervised Classification
by: Abburi, VSS Tejaswi, et al.
Published: (2026)

Semi-LAR: Semi-supervised Contrastive Learning with Linear Attention for Removal of Nighttime Flares
by: Zhu, Xiyu, et al.
Published: (2026)

Diff-CL: A Novel Cross Pseudo-Supervision Method for Semi-supervised Medical Image Segmentation
by: Guo, Xiuzhen, et al.
Published: (2025)

Graph-Weighted Contrastive Learning for Semi-Supervised Hyperspectral Image Classification
by: Zhang, Yuqing, et al.
Published: (2025)

SM2C: Boost the Semi-supervised Segmentation for Medical Image by using Meta Pseudo Labels and Mixed Images
by: Wang, Yifei, et al.
Published: (2024)

SSFlowNet: Semi-supervised Scene Flow Estimation On Point Clouds With Pseudo Label
by: Chen, Jingze, et al.
Published: (2023)

Pairwise Similarity Regularization for Semi-supervised Graph Medical Image Segmentation
by: Zhou, Jialu, et al.
Published: (2025)

Slimmable Networks for Contrastive Self-supervised Learning
by: Zhao, Shuai, et al.
Published: (2022)

Weakly Supervised Contrastive Adversarial Training for Learning Robust Features from Semi-supervised Data
by: Zhang, Lilin, et al.
Published: (2025)

DyConfidMatch: Dynamic Thresholding and Re-sampling for 3D Semi-supervised Learning
by: Chen, Zhimin, et al.
Published: (2024)

Gradient-based Sampling for Class Imbalanced Semi-supervised Object Detection
by: Li, Jiaming, et al.
Published: (2024)

PEPL: Precision-Enhanced Pseudo-Labeling for Fine-Grained Image Classification in Semi-Supervised Learning
by: Tian, Bowen, et al.
Published: (2024)